Update README.md

README.md

@@ -1,7 +1,7 @@
 ---
 language:
-- it
 - en
+- it
 library_name: transformers
 license: apache-2.0
 tags:
@@ -20,11 +20,14 @@ model-index:
 
 # Veronica — Custom Causal LM (decoder-only)
 
-**Veronica** è un modello *decoder-only* custom, progettato per massimizzare la **profondità effettiva** e la qualità per token con risorse contenute.  
-Architettura: **32 layer × 1024 hidden × 16 heads, GQA=4**, **RoPE (θ=1e6) + YaRN scaling** per contesto lungo **32k**.  
-Attenzione: **DuoAttention** (stream vs full window) + **SEAL** scaling sulle retrieval-heads. **RMSNorm** + **SwiGLU**.
+**Veronica** is a custom *decoder-only* large language model, designed to maximize **depth efficiency** and token-level reasoning quality under limited resources.  
+It features **32 layers × 1024 hidden × 16 heads (GQA=4)**, extended context via **RoPE (θ=1e6) + YaRN scaling** up to **32k tokens**, and advanced attention routing with **DuoAttention** and **SEAL scaling**.
 
-> **Stato**: prototipo in pretraining. Questa repo pubblica **codice + config + tokenizer** per il caricamento via `trust_remote_code=True`. I pesi saranno pubblicati successivamente.
+> **Status:** prototype under pretraining.  
+> This repository currently provides **code, config, and tokenizer** to load Veronica with `trust_remote_code=True`.  
+> Model weights will be released in a future update.
+
+---
 
 ## Quickstart
 
@@ -40,6 +43,6 @@ model = AutoModelForCausalLM.from_pretrained(
     device_map="auto",
 )
 
-prompt = "Spiega in modo semplice cos'è Veronica:"
+prompt = "Explain in simple terms what Veronica is:"
 out = model.generate(**tok(prompt, return_tensors="pt").to(model.device))
-print(tok.decode(out[0], skip_special_tokens=True))
+print(tok.decode(out[0], skip_special_tokens=True))